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  Real-time functional magnetic resonance imaging: methods and applications

Weiskopf, N., Sitaram, R., Josephs, O., Veit, R., Scharnowski, F., Goebel, R., et al. (2007). Real-time functional magnetic resonance imaging: methods and applications. Magnetic Resonance Imaging, 25(6), 989-1003.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0003-E16F-3 Version Permalink: http://hdl.handle.net/21.11116/0000-0003-E170-0
Genre: Conference Paper

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 Creators:
Weiskopf, N, Author
Sitaram, R, Author              
Josephs, O, Author
Veit, R1, 2, Author              
Scharnowski, F, Author
Goebel, R, Author
Birbaumer, N, Author
Deichmann, R, Author
Mathiak, K, Author
Affiliations:
1Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794              
2Former Department MRZ, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_2528700              

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Free keywords: Real-time functional magnetic resonance imaging; Brain–computer interface; Neurofeedback; Quality assurance; Functional localizer; Teaching; Review
 Abstract: Functional magnetic resonance imaging (fMRI) has been limited by time-consuming data analysis and a low signal-to-noise ratio, impeding online analysis. Recent advances in acquisition techniques, computational power and algorithms increased the sensitivity and speed of fMRI significantly, making real-time analysis and display of fMRI data feasible. So far, most reports have focused on the technical aspects of real-time fMRI (rtfMRI). Here, we provide an overview of the different major areas of applications that became possible with rtfMRI: online analysis of single-subject data provides immediate quality assurance and functional localizers guiding the main fMRI experiment or surgical interventions. In teaching, rtfMRI naturally combines all essential parts of a neuroimaging experiment, such as experimental design, data acquisition and analysis, while adding a high level of interactivity. Thus, the learning of essential knowledge required to conduct functional imaging experiments is facilitated. rtfMRI allows for brain-computer interfaces (BCI) with a high spatial and temporal resolution and whole-brain coverage. Recent studies have shown that such BCI can be used to provide online feedback of the blood-oxygen-level-dependent signal and to learn the self-regulation of local brain activity. Preliminary evidence suggests that this local self-regulation can be used as a new paradigm in cognitive neuroscience to study brain plasticity and the functional relevance of brain areas, even being potentially applicable for psychophysiological treatment.

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Language(s): eng - English
 Dates: 2007-07
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: -
 Identifiers: DOI: 10.1016/j.mri.2007.02.007
 Degree: -

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Title: International School on Magnetic Resonance and Brain Function 2007
Place of Event: Erice, Italy
Start-/End Date: 2007-05-21 - 2007-05-28

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Title: Magnetic Resonance Imaging
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: New York : Elsevier
Pages: - Volume / Issue: 25 (6) Sequence Number: - Start / End Page: 989 - 1003 Identifier: ISSN: 0730-725X
CoNE: https://pure.mpg.de/cone/journals/resource/954925533026